MIDAS TRACKS


The scope of this conference is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in various topics of Engineering and Technology. It allows participants an opportunity to discuss the recent developments in the field of solidification computer science and management and review challenges faced by the community in the 21st century. The conference consists of invited
Paper submission allow only through easychair portal. Click to Submit




Authors are invited to submit original research contributions not concurrently submitted elsewhere. Normal length papers should be between 10 to 12 pages formatted according to Springer’s “Algorithms for Intelligent Systems” style. The file format for submissions is Adobe Portable Document Format (PDF). Other formats will not be accepted.



Track 1: Machine Learning Algorithms


• Computational Intelligence
• Cognitive Intelligence
• Ambient Intelligence
• Deep Learning
• Intelligent Systems


Track 2: Data Analytics and Optimization


• Data Pre-Processing
• Big Data Analytics
• Soft Computing
• Evolutionary Computing
• Nature Inspired Computing
• Predictive Analysis


Track 3: Machine Intelligence Applications


• Image Processing
• Natural Language Processing
• Computer Vision
• Sentiment Analysis
• Search Engine Optimization
• Speech and Gesture Analysis
• Augmented/Virtual Realty


Track 4: Machine Intelligence in Interdisciplinary Areas


• AI in Legal
• AI in Healthcare and Medicine
• Smart Society
• Smart Farming
• IoT
• Cyber Physical System
• Robotics


Other Topics


• Deep Learning for Data Intelligence
• AI for Business data analytics
• Performance Tuning and optimization for Big Data Using AI.
• Data Science Visualization using AI
• Optimization for machine Learning and Data mining in Big Data
• AI in securing Data
• Data Science for Industry 4.0
• Data Science and AI in e-Government and Society
• Big Data Fusion using AI
• AI for Big Social Data Analysis
• Artificial Intelligence for knowledge management and big data, data analytics
• AI for Data Stream Mining
• AI for massive scale data science
• AI in Data informatics
• IoT sensor Data Analysis and Fusion
• Big Special Data Analytics
• Cost Modeling using AI
• Case studies of use of data science and AI applications in engineering, healthcare, business
• AI applications and Innovations
• Research trends, challenges, and the future of AI in Data Science.